AIMC Topic: Tomography, X-Ray Computed

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Deep learning based reconstruction enables high-resolution electrical impedance tomography for lung function assessment.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recently, deep learning based methods have shown potential as alternative approaches for lung time difference electrical impedance tomography (tdEIT) reconstruction other than traditional regularized least square methods, that have inherent severe il...

Mining Whole-liver Information with Deep Learning for Preoperatively Predicting HCC Recurrence-free Survival.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Hepatocellular carcinoma (HCC) is globally a leading cause of cancer death. Non-invasive pre-operative prediction of HCC recurrence-free survival (RFS) after resection is essential but remains challenging. Previous models based on medical imaging foc...

Deep-learning reconstruction for the evaluation of lumbar spinal stenosis in computed tomography.

Medicine
To compare the quality and interobserver agreement in the evaluation of lumbar spinal stenosis (LSS) on computed tomography (CT) images between deep-learning reconstruction (DLR) and hybrid iterative reconstruction (hybrid IR). This retrospective stu...

[Metal artifact reduction and clinical verification in oral and maxillofacial region based on deep learning].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
To construct a kind of neural network for eliminating the metal artifacts in CT images by training the generative adversarial networks (GAN) model, so as to provide reference for clinical practice. The CT data of patients treated in the Department ...

Deep Learning Method for Estimation of Morphological Parameters Based on CT Scans.

Studies in health technology and informatics
In this study, we propose a Convolutional Neural Network (CNN) with an assembly of non-linear fully connected layers for estimating body height and weight using a limited amount of data. This method can predict the parameters within acceptable clinic...

Assessing the FAIRness of Deep Learning Models in Cardiovascular Disease Using Computed Tomography Images: Data and Code Perspective.

Studies in health technology and informatics
The interest in the application of AI in medicine has intensely increased over the past decade with most of the changes in the past five years. Most recently, the application of deep learning algorithms in prediction and classification of cardiovascu...

Deep-Learning Segmentation of Urinary Stones in Noncontrast Computed Tomography.

Journal of endourology
Noncontrast CT (NCCT) relies on labor-intensive examinations of CT slices to identify urolithiasis in the urinary tract, and, despite the use of deep-learning algorithms, false positives remain. A total of 410 NCCT axial scans from patients undergo...